Author

D. O'Meally

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Cancer Biology· 3

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 3 Approach:statistical model· 3 Research Focus:trajectory inference· 3 Organism:mouse· 2 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

G. Marcucci· 3 shared R. C. Rockne· 3 shared S. Branciamore· 3 shared Y.-H. Kuo· 3 shared D. E. Frankhouser· 2 shared L. Uechi· 2 shared N. Carlesso· 2 shared S. Forman· 2 shared

Activity by Year

2019-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 43 mutual co-author links

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3 shared papersCancer Biology

G. Marcucci

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3 papers

Recent·Most cited

State-transition Modeling of Blood Transcriptome Predicts Disease Evolution and Treatment Response in Chronic Myeloid Leukemia

D. E. Frankhouser, R. C. Rockne, L. Uechi, D. Zhao, S. Branciamore, D. O'Meally, J. Irizarry, L. Ghoda, H. Ali, J. Trent, S. Forman, Y.-H. Fu, Y.-H. Kuo, B. Zhang, G. Marcucci

The paper uses transcriptome-based state-transition models to predict CML disease progression and treatment response using time-sequential blood samples from mice.

bioRxiv · Oct 11, 2023Cancer Biology

State-Transition Analysis of Time-Sequential microRNA Expression Predicts Development of Acute Myeloid Leukemia

D. E. Frankhouser, D. O'Meally, S. Branciamore, L. Uechi, H. Qin, X. Wu, N. Carlesso, G. Marcucci, Y.-H. Kuo, R. C. Rockne

This study uses time-sequential miRNA expression data from a mouse AML model to identify state transitions during leukemogenesis and shows the model predicts time to AML development.

bioRxiv · Mar 2, 2021 · PreprintCancer Biology

State-Transition Analysis of Time-Sequential Gene Expression Identifies Critical Points That Predict Leukemia Development

R. C. Rockne, S. Branciamore, J. Qi, D. Frankhouser, D. O'Meally, W.-K. Hua, G. J. Cook, L. Zhang, E. Carnahan, A. Marom, H. Wu, D. Maestrini, X. Wu, Y.-C. Yuan, Z. Liu, , G. Marcucci

The paper models leukemia transcriptome dynamics in a state-space to identify critical points that predict disease development.

bioRxiv · Jun 4, 2019 · PreprintCancer Biology